



'''simple docstring'''



import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand
def        UpperCAmelCase (    A	:					str					):
							return EnvironmentCommand()
def        UpperCAmelCase (    A	:					List[str]					):
							return EnvironmentCommand(args.accelerate_config_file					)






class 						lowerCamelCase_				(       snake_case_      ):







						@staticmethod
						def        __lowercase     (	lowerCAmelCase__ :   ArgumentParser					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      parser.add_parser('''env'''					)
													download_parser.set_defaults(func=lowerCAmelCase__					)
													download_parser.add_argument(
													    '''--accelerate-config_file'''					,     default=lowerCAmelCase__					,     help='''The accelerate config file to use for the default values in the launching script.'''					,     )
													download_parser.set_defaults(func=lowerCAmelCase__					)







						def __init__(	self :   int					,     lowerCAmelCase__ :   Dict					,     *lowerCAmelCase__ :   Tuple					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      accelerate_config_file







						def        __lowercase     (	self :   List[str]					):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE       :   str         =      '''not installed'''
													if is_safetensors_available():
																				import safetensors

																				SCREAMING_SNAKE_CASE       :   Optional[Any]         =      safetensors.__version__
													elif importlib.util.find_spec('''safetensors'''					) is not None:
																				import safetensors

																				SCREAMING_SNAKE_CASE       :   Tuple         =      F"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

													SCREAMING_SNAKE_CASE       :   Optional[int]         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      '''not found'''
													if is_accelerate_available():
																				import accelerate
																				from accelerate.commands.config import default_config_file, load_config_from_file

																				SCREAMING_SNAKE_CASE       :   List[str]         =      accelerate.__version__
																				# Get the default from the config file.
																				if self._accelerate_config_file is not None or os.path.isfile(lowerCAmelCase__					):
																											SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      load_config_from_file(self._accelerate_config_file					).to_dict()

																				SCREAMING_SNAKE_CASE       :   List[str]         =      (
																				    '''\n'''.join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]					)
																				    if isinstance(lowerCAmelCase__					,     lowerCAmelCase__					)
																				    else F"""\t{accelerate_config}"""
																				)

													SCREAMING_SNAKE_CASE       :   Tuple         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   Optional[int]         =      '''NA'''
													if is_torch_available():
																				import torch

																				SCREAMING_SNAKE_CASE       :   int         =      torch.__version__
																				SCREAMING_SNAKE_CASE       :   List[str]         =      torch.cuda.is_available()

													SCREAMING_SNAKE_CASE       :   Dict         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   int         =      '''NA'''
													if is_tf_available():
																				import tensorflow as tf

																				SCREAMING_SNAKE_CASE       :   Any         =      tf.__version__
																				try:
																											# deprecated in v2.1
																											SCREAMING_SNAKE_CASE       :   List[str]         =      tf.test.is_gpu_available()
																				except AttributeError:
																											# returns list of devices, convert to bool
																											SCREAMING_SNAKE_CASE       :   Dict         =      bool(tf.config.list_physical_devices('''GPU'''					)					)

													SCREAMING_SNAKE_CASE       :   List[Any]         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   List[str]         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   str         =      '''not installed'''
													SCREAMING_SNAKE_CASE       :   List[Any]         =      '''NA'''
													if is_flax_available():
																				import flax
																				import jax
																				import jaxlib

																				SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      flax.__version__
																				SCREAMING_SNAKE_CASE       :   Dict         =      jax.__version__
																				SCREAMING_SNAKE_CASE       :   List[Any]         =      jaxlib.__version__
																				SCREAMING_SNAKE_CASE       :   Any         =      jax.lib.xla_bridge.get_backend().platform

													SCREAMING_SNAKE_CASE       :   int         =      {
													    '''`transformers` version''': version,
													    '''Platform''': platform.platform(),
													    '''Python version''': platform.python_version(),
													    '''Huggingface_hub version''': huggingface_hub.__version__,
													    '''Safetensors version''': F"""{safetensors_version}""",
													    '''Accelerate version''': F"""{accelerate_version}""",
													    '''Accelerate config''': F"""{accelerate_config_str}""",
													    '''PyTorch version (GPU?)''': F"""{pt_version} ({pt_cuda_available})""",
													    '''Tensorflow version (GPU?)''': F"""{tf_version} ({tf_cuda_available})""",
													    '''Flax version (CPU?/GPU?/TPU?)''': F"""{flax_version} ({jax_backend})""",
													    '''Jax version''': F"""{jax_version}""",
													    '''JaxLib version''': F"""{jaxlib_version}""",
													    '''Using GPU in script?''': '''<fill in>''',
													    '''Using distributed or parallel set-up in script?''': '''<fill in>''',
													}

													print('''\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'''					)
													print(self.format_dict(lowerCAmelCase__					)					)

													return info







						@staticmethod
						def        __lowercase     (	lowerCAmelCase__ :   List[Any]					):

													"""simple docstring"""
													return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]					) + "\n"









'''simple docstring'''



from __future__ import annotations
def        UpperCAmelCase (    A	:					list[int]       ,		A	:					int					):
							if len(A					) < k or k < 0:
														raise ValueError('''Invalid Input'''					)
							SCREAMING_SNAKE_CASE       :   Dict         =      sum(array[:k]					)
							for i in range(len(A					) - k					):
														SCREAMING_SNAKE_CASE       :   Optional[Any]         =      current_sum - array[i] + array[i + k]
														SCREAMING_SNAKE_CASE       :   Union[str, Any]         =      max(A       ,		A					)
							return max_sum


if __name__ == "__main__":
							from doctest import testmod
							from random import randint

							testmod()
							lowerCAmelCase_  :							Optional[int]             =    [randint(-1000, 1000) for i in range(100)]
							lowerCAmelCase_  :							Optional[int]             =    randint(0, 110)
							print(f'The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}')




